1. Field of the Invention
The present invention relates to knowledge bases, and more particularly to improved methods for finding relevant content in knowledge bases.
2. Description of the Related Art
A knowledge base is a type of system for knowledge management. It provides the means for the computerized collection, organization, and retrieval of knowledge in a particular area. Typically, knowledge bases have carefully written articles, pages, documents or items that are kept up to date, an information retrieval system (such as a search engine), and a carefully designed content format and classification structure. A knowledge base may further use an ontology to specify its structure (entity types and relationships) and classification scheme. An ontology, together with a set of instances of its classes, constitutes a knowledge base.
Users of a knowledge base often desire to find content that is relevant to a given page, article, document or other knowledge base item (collectively referred to as “knowledge base item”). A knowledge base search engine is typically used to perform this function. Knowledge base search engines parse a given knowledge base item into keywords. The search engine compares the search terms, i.e., keywords with the keywords within other items in the knowledge base and determines whether the search terms match or are found within any of the items within the knowledge base. When a match is found, a list of the items that matches the search terms is displayed for the user. The returned list is typically presented without any structure. Typically, knowledge base search engines return any item containing a keyword that is found anywhere within the items. However, knowledge base search engines are unable to always return results that are relevant to the knowledge base item in which the user was initially interested.
There are other limitations with present knowledge base search engines and the methods by which knowledge bases being accessed by these search engines provide data to the requestor. For example, knowledge base search engines often return a long list of search results containing a lot of noise items. Junk results often greatly out-number the results in which the user is interested, and the results of interest are occasionally embedded deep within the list of provided results. From the user's perspective, the results of such searches often are too large to investigate, while at the same time the results do not contain enough relevant items to be useful. Most users are only willing to look at the first few tens of results. Further, no assistance is given by the search engine to help the user understand how the resulting items relate to each other, or to the task that the user is trying to accomplish. Thus, the results of such searches are often unusable because hundreds of items are returned but the type of information presented in each item is unspecified.
In order to provide more information about knowledge base items, users may create links between items. Links can be useful. However, links don't indicate why items were linked. This decreases the value of a link in discerning the relevance of an item. Another common method of providing more information about knowledge base items involves using metadata. Content providers may create metadata along with content, in addition to including links to other knowledge base items having the same metadata. Although this arrangement may be used to show similarities between items, this approach can often lead to search results that include unrelated content.